The objectives of this proposal are to develop multiscale models of lung injury caused by either primary Influenza infection or secondary pneumonia, and identify from simulations optimal intervention strategies in non-trivial situations, such as highly virulent pathogens and sub-optimal immunization. This effort will include the development of reduced and more detailed models of the host-influenza interaction, the innate and adaptive immune response and pulmonary gas exchange under evolving lung injury. These models will be calibrated with prospective data from a series of experiment of mice infected with strains of Influenza of varying virulence, with or without immunization, and with or without antiviral pharmacotherapy. This group of interdisciplinary investigators has a track record of several years of developing theoretical and animal models of infection and inflammation, and of prior collaboration. When completed, this proposal will have accomplished three important scientific goals: (1) provide a solid biological basis for assumptions used in the design of individual and population-based containment strategies of highly virulent Influenza, (2) provide a foundation for further studies of multiscale whole organ models including mechanisms of organ failure and (3) provide quantitative methods to assess the uncertainty associated with model predictions when such models are calibrated from imperfect or sparse empirical data. The proposed activities will involve the training post-doctoral fellows, graduate and undergraduate students in an interdisciplinary environment strongly dedicated to scientific dissemination to clinicians, biologists and quantitative scientists. This proposal will confirm these investigators strong continued commitment to the training of women scientists, and will reach out to underrepresented minorities, particularly at the undergraduate level. This project will also enhance existing resources such as the XPP freeware, widely used by trainees and accomplished scientists, web accessible resource (models and software), and web based data repositories. It is the belief of this group of investigator that mathematical modeling and computation are essential tools in translating large streams of data in knowledge that will benefit patient care and societal preparedness to potentially catastrophic emerging infectious threats.